Biomarker-Based Risk Prediction of Incident Heart Failure in Pre-Diabetes and Diabetes

Combined Risk Stratification With Patient Characteristics and Biomarkers in Patients Treated With the Impella for Cardiogenic Shock

BACKGROUND

In patients with cardiogenic shock (CS), a percutaneous microaxial ventricular assist device (Impella, Abiomed, Danvers, MA) is a choice for temporary mechanical circulatory support. Given the high morbidity and mortality in this patient population, early risk stratification is relevant when making treatment decisions.

METHODS

Using nationwide registry data between February 2020 and December 2022 in Japan, we included a total of 4122 patients with cardiogenic shock treated with the Impella devices. Using logistic regression analysis, we incorporated patient characteristics and biomarkers to develop a risk-stratifying model for in-hospital mortality. The model was also tested if applicable to composite outcomes of in-hospital death and major complications.

RESULTS

Of the 4122 patients with cardiogenic shock, the Impella was indicated for acute myocardial infarction in 2575 (62.5%). Multivariable analysis identified 4 patient characteristics (age, body mass index, out-of-hospital cardiac arrest, and blood pressure) and 6 biomarkers (lactate, lactate dehydrogenase, creatinine, total bilirubin, albumin, and creatinine kinase) with cutoff values as factors significantly associated with in-hospital mortality. We developed a risk-stratifying model using the 10 variables, which was predictive of in-hospital death (area under the curve, 0.711; P<0.001). Adding biomarkers to patient characteristics significantly improved the diagnostic accuracy (area under the curve, from 0.649 to 0.711; P<0.001). This risk score was also predictive of death and major complications (area under the curve, 0.680; P<0.001).

CONCLUSIONS

In patients with cardiogenic shock treated with the Impella devices, our risk-stratifying system, consisting of 4 patient characteristics and 6 biomarkers, strongly correlated with in-hospital mortality, potentially facilitating clinical decision-making.

Mechanisms of diabetic cardiomyopathy: Focus on inflammation

PURPOSE OF REVIEW

Type 2 diabetes (T2D) significantly increases the risk of heart failure (HF), either through the progression of coronary artery disease (CAD) or through direct myocardial alterations, termed diabetic cardiomyopathy. This review examines key pathophysiological mechanisms underlying diabetic cardiomyopathy, focusing on the role of inflammation. It also addresses diagnostic and therapeutic approaches to mitigate myocardial damage in T2D.

RECENT FINDINGS

Chronic low-grade inflammation is considered as a major contributor to diabetic cardiomyopathy. T2D-related factors, including hyperglycemia and insulin resistance, activate inflammatory pathways that worsen myocardial dysfunction. Despite advances in understanding these mechanisms, no therapies specifically targeting the cardiac changes in T2D have been identified.

SUMMARY

While significant advances have been made in elucidating the inflammatory mechanisms contributing to diabetic cardiomyopathy, therapeutic advancements remain limited, potentially due to an incomplete understanding of regulatory pathways. A comprehensive investigation into the specific roles of immune cells and inflammatory mediators in diabetic cardiomyopathy is essential for identifying novel therapeutic targets. Expanding our knowledge of these molecular mechanisms has the potential to facilitate the development of innovative therapeutic strategies, thereby improving clinical outcomes in patients with T2D.

Impact of Metabolic Dysfunction-associated Steatotic Liver Disease on Cardiovascular Structure, Function, and the Risk of Heart Failure

Mounting evidence has established metabolic dysfunction-associated steatotic liver disease (MASLD) as an independent risk factor for heart failure (HF), particularly HF with preserved ejection fraction (HFpEF). In this narrative review we explore the impact of MASLD on cardiovascular structure and function. We summarize findings from multiple cohort studies demonstrating that MASLD is associated with distinct patterns of adverse cardiac remodeling, including increased left ventricular concentricity and impaired diastolic function. These subclinical changes in cardiac structure and function often precede overt HF development and appear to occur in the context of multiple interconnected pathways involving metabolic dysfunction, systemic inflammation, adipose tissue dysregulation, vascular dysfunction, and altered hepatic hemodynamics. Early identification of cardiac structural and functional abnormalities through systematic screening may enable timely intervention in this high-risk population. Lifestyle modifications remain foundational, but achieving and maintaining significant weight loss is challenging. Recent clinical trials have shown promising results with cardiometabolic agents, particularly glucagon-like protein 1 receptor agonists, which demonstrate significant weight loss and hepatic and cardiovascular benefits. Despite these advances, key knowledge gaps remain regarding optimal screening strategies, mechanisms linking MASLD to HF, and targeted therapeutic approaches. Addressing these gaps will be essential for developing effective prevention and treatment strategies in this high-risk population.

Diabetes, Subclinical Myocardial Injury or Stress, and Risk of Heart Failure Subtypes: The Jackson Heart Study

OBJECTIVE

To assess the extent to which the concomitant presence of subclinical myocardial injury or stress and diabetes affects the risk of heart failure (HF) subtypes.

RESEARCH DESIGN AND METHODS

The Jackson Heart Study included Black adults, categorized based on diabetes status, high-sensitivity cardiac troponin I (hs-cTnI), and brain natriuretic peptide (BNP) levels. Subclinical myocardial injury was defined as hs-cTnI ≥4 ng/L in women and ≥6 ng/L in men, and subclinical myocardial stress as BNP ≥35 pg/mL. The study outcomes included incident HF, HF with preserved ejection fraction (HFpEF), and HF with reduced ejection fraction (HFrEF).

RESULTS

Among 3,484 participants (mean age 54.6 years, 63.2% women, 22.3% with diabetes, 26.4% with subclinical myocardial injury, 9.4% with subclinical myocardial stress), 306 developed HF (151 HFpEF and 139 HFrEF) over 12 years. Compared with individuals with no diabetes and no subclinical myocardial injury at recruitment, participants with diabetes and subclinical myocardial injury had a higher HF risk (hazard ratio [HR] 3.84, 95% CI 2.60-5.66), HFpEF (HR 3.68, 95% CI 2.13-6.36), and HFrEF (HR 4.26, 95% CI 2.40-7.53). The HRs associated with the presence of diabetes and subclinical myocardial stress versus their joint absence were 4.03 (95% CI 2.50-6.51), 5.71 (95% CI 3.11-10.47), and 2.13 (95% CI 0.88-5.17) for HF, HFpEF, and HFrEF, respectively. There was no significant diabetes status and cardiac biomarkers interaction.

CONCLUSIONS

Both diabetes and subclinical myocardial damage significantly increase the risk of all HF types among Black individuals.

Construction of a prediction model for coronary heart disease in type 2 diabetes mellitus: a cross-sectional study

Type 2 diabetes mellitus (T2DM), as a globally prevalent metabolic disorder, is continuously rising in prevalence and significantly increases the risk of developing coronary heart disease (CHD). Studies have shown that the risk of CHD is higher in T2DM patients compared to those without diabetes, making early identification and prevention essential. Therefore, establishing an effective prediction model to identify high-risk individuals for CHD among T2DM patients is crucial. This study aims to develop and validate a prediction model for coronary heart disease in patients with type 2 diabetes mellitus, accurately identifying high-risk individuals to support early intervention and personalized treatment. The study included 423 patients with type 2 diabetes mellitus (T2DM) who were hospitalized in the endocrinology department of a tertiary hospital in Anhui Province between February 1, 2023, and February 1, 2024. Based on the presence of hypertension, patients were divided into a T2DM with coronary heart disease (CHD) group (193 patients) and a T2DM group (230 patients). Data were collected through questionnaires and clinical indicators. Univariate and multivariate logistic regression analyses were used to identify significant predictors, and the model was validated. Model performance was evaluated using the ROC curve and AUC value. Hypertension, smoking, neuropathy, vascular complications, cerebral infarction, bilateral lower extremity arteriosclerosis, microalbuminuria, and elevated uric acid levels. were identified as significant predictors for T2DM with hypertension. The AUC of the prediction model was 0.83, indicating good predictive performance. The prediction model developed in this study effectively identifies high-risk patients with T2DM and CHD, providing a reliable tool for clinical use. This model facilitates early intervention and personalized treatment for hypertension, smoking, neuropathy, vascular complications, cerebral infarction, bilateral lower extremity arteriosclerosis, microalbuminuria, and elevated uric acid levels, improving overall health outcomes for patient.

A machine learning tool for identifying newly diagnosed heart failure in individuals with known diabetes in primary care

AIMS

We aimed to create a predictive model utilizing machine learning (ML) to identify new cases of congestive heart failure (CHF) in individuals with diabetes in primary health care (PHC) through the analysis of diagnostic data.

METHODS

We used a sex- and age-matched case-control design. Cases of new CHF were identified across all outpatient care settings 2015-2022 (n = 9098). We included individuals 30 years and above, by sex and age groups of 30-65 years and >65 years. The controls (five per case) were sampled from the individuals in 2015-2022 without CHF at any time between 2010 and 2022, in total 45 490. From the stochastic gradient boosting (SGB) technique model, we obtained a rank of the 10 most important factors related to newly diagnosed CHF in individuals with diabetes, with the normalized relative influence (NRI) score and a corresponding odds ratio of marginal effects (ORME). Area under curve (AUC) was calculated.

RESULTS

For women 30-65 years and >65 years, we identified 488 and 3240 new cases of CHF, respectively, and men 30-65 years and >65 years 1196 and 4174 new cases. Among the 10 most important factors in the four groups (divided by sex and lower and higher age) for newly diagnosed CHF, we found the number of visits 12 months before diagnosis (NRI 44.3%-55.9%), coronary artery disease (NRI 2.9%-7.8%), atrial fibrillation and flutter (NRI 6.6%-12.2%) and 'abnormalities of breathing' (ICD-10 code R06) (NRI 2.6%-4.4%) were predictive in all groups. For younger women, a diagnosis of COPD (NRI 2.7%) contributed to the predictive effect, while for older women, oedema (NRI 3.1%) and number of years with diabetes (NRI 3.5%) contributed to the predictive effect. For men in both age groups, chronic renal disease had predictive effect (NRI 3.9%-5.1%) The model prediction of CHF among patients with diabetes was high, AUC around 0.85 for the four groups, and with sensitivity over 0.783 and specificity over 0.708 for all four groups.

CONCLUSIONS

An SGB model using routinely collected data about diagnoses and number of visits in primary care, can accurately predict risk for diagnosis of heart failure in individuals with diabetes. Age and sex difference in predictive factors warrant further examination.

The correlation between high-sensitivity cardiac troponin levels in diabetic patients' serum and lower limb lesions: based on NHANES data

Objective

To evaluate the association of hypersensitive cardiac troponin (hs-cTnT), a biomarker of myocardial injury, with diabetic lower extremity disease in American adults.

Methods

We conducted a cross-sectional study (unweighted N=1,196) of diabetic patients aged 40 years or older who participated in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2004. Logistic regression was used to assess the association of hs-cTnT with lower extremity disease, including peripheral neuropathy (as assessed by monofilament test), peripheral artery disease (as assessed by ankle-brachial index), history of foot ulcers, or amputation. All analyses are weighted.

Results

The prevalence rate of diabetic lower extremity disease was 41.6%. Adjusted hs-cTnT was significantly associated with lower limb disease in adults with diabetes. There is interaction between chronic kidney disease and hs-cTnT, which strongly interferes with the correlation between hs-cTnT and lower extremity lesions in diabetic patients.

Conclusions

Our study suggests the usefulness of hs-cTnT as a biomarker for lower extremity lesions in adults with diabetes and highlights the potential direct interaction of hs-cTnT with chronic kidney disease.

American Diabetes Association Professional Practice Committee, ElSayed NA, McCoy RG, Aleppo G, Balapattabi K, Beverly EA, Briggs Early K, Bruemmer D, Das SR, Echouffo-Tcheugui JB, Ekhlaspour L, Garg R, Khunti K, Kosiborod MN, Lal R, Lingvay I, Matfin G, Pandya N, Pekas EJ, Pilla SJ, Polsky S, Segal AR, Seley JJ, Stanton RC, Bannuru RR. 10. Cardiovascular Disease and Risk Management: Standards of Care in Diabetes-2025

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A Saudi Heart Association Position Statement on Cardiovascular Diseases and Diabetes Mellitus

Background

Cardiovascular disease (CVD) and diabetes mellitus are prominent public health concerns in Saudi Arabia owing to their increasingly high prevalence and burden. Based on this, the Saudi Heart Association (SHA) set out to develop an official position statement on CVD and diabetes mellitus, with a focus on the prevention and management of these conditions and relevant special populations in the context of Saudi Arabia.

Methods

A multidisciplinary panel of experts met under the auspices of the SHA in a series of meetings to review and discuss available evidence on the prevention and management of comorbid CVD and diabetes mellitus. Specialized subcommittees reviewed the data and offered context-specific recommendations (taking into account Saudi population characteristics, local healthcare system, available resources and medical expertise), which were later approved by the full expert panel.

Results and conclusions

The prevalence of diabetes mellitus and CVD is alarming in the Saudi Arabian population. Diabetes mellitus and CVD are interconnected on several levels, including cellular and molecular events as well as epigenetic and genetic mechanisms. Screening for CVD is a priority for patients with diabetes and concomitant risk factors. The expert panel also recommends aggressive management of high blood pressure and dyslipidemia in addition to lifestyle changes and achieving glycemic targets for the prevention of CVD in patients with diabetes. Some glucose-lowering drug classes, namely SGLT2-inhibitors and GLP-1 receptor agonists, offer significant benefits on the level of cardiovascular risk reduction and are thus a powerful addition to the clinical management armamentarium in CVD and diabetes. Special consideration is also advised for patient populations with distinct clinical presentation and needs, such as coronary artery disease, heart failure, and chronic kidney disease, among others.

Myocardial Abnormalities Across the AHA/ACC Stages of Heart Failure in Patients With Diabetes

Background

Cardiac magnetic resonance imaging (CMR) could serve as a robust tool for comprehensive evaluation of early changes across heart failure (HF) stages classified by the American Heart Association/American College of Cardiology guideline in diabetes mellitus (DM).

Objectives

The authors aimed to explore phenotypic imaging features characterizing DM participants at different HF stages by CMR.

Methods

DM participants with preserved ejection fraction who underwent CMR examination between January 2020 and December 2021 were evaluated. Left ventricular strain analysis and myocardial fibrosis was evaluated by CMR.

Results

A total of four hundred seventy-five DM participants at different HF stages (mean age 56 ± 12 years; 326 men) and 78 healthy control subjects were evaluated. Significantly decreased absolute strain values with rising HF stage were identified in DM. In addition, early diastolic strain rates were significantly lower in stage B and C HF than in stage A HF and control subjects. Myocardial extracellular volume increased with advancing HF stage in DM (stage A, 27.0% ± 2.9%; stage B, 29.1% ± 3.5%; stage C, 30.5% ± 4.1%; P < 0.05). In multivariable logistic regression analysis, early diastolic longitudinal strain rate (OR: 2.184; 95% CI: 1.378-3.461; P < 0.001) was a significant contributor that independently distinguished DM participants at stage A from control subjects, with an area under the receiver-operating characteristic curve of 0.726. For global longitudinal strain and extracellular volume, each 1% increase was associated with 1.333 and 1.300 times adjusted odds of diagnosis of stage B HF (both P < 0.05).

Conclusions

Subclinical dysfunction and myocardial fibrosis derived from CMR were progressively remarkable with advancing HF stage in DM. Comprehensive CMR provided sensitive tools for better delineation of DM patients with pre-HF and at risk for HF.

Precision Medicine for Cardiovascular Prevention and Population Health: A Bridge Too Far?

Precision medicine aims to provide personalized clinical care guided by tools that reflect underlying pathophysiology. The need for such an approach has never been greater in cardiovascular medicine, given the large number of guideline-directed medical therapies available. However, progress has been modest to date with few precision tools available for clinicians. Arguably, cardiovascular prevention and population health are poised for innovation to guide evaluation and management, as these areas are already informed by risk-assessment, but limited by the use of crude assessment tools with marginal performance. Risk assessment in prevention and population health may be improved with the use of genetics, circulating biomarkers, and imaging, leading to outcome-specific risk-prediction and enhanced phenotyping. Personalized management matching therapy to risk profile can be then implemented for either individuals or groups, improving cost-effectiveness and risk-benefit. Here, we explore this precision-like approach, including available tools, potential applications, and future perspectives for cardiovascular prevention and population health management.

Leveraging calcium score CT radiomics for heart failure risk prediction

Studies have used extensive clinical information to predict time-to-heart failure (HF) in patients with and without diabetes mellitus (DM). We aimed to determine a screening method using only computed tomography calcium scoring (CTCS) to assess HF risk. We analyzed CTCS scans from 1,998 patients (336 with type 2 diabetes) from a no-charge coronary artery calcium score registry (CLARIFY Study, Clinicaltrials.gov NCT04075162). We used deep learning to segment epicardial adipose tissue (EAT) and engineered radiomic features of calcifications ("calcium-omics") and EAT ("fat-omics"). We developed models incorporating radiomics to predict risk of incident HF in patients with and without type 2 diabetes. At a median follow-up of 1.7 years, 5% had incident HF. In the overall cohort, fat-omics (C-index: 77.3) outperformed models using clinical factors, EAT volume, Agatston score, calcium-omics, and calcium-and-fat-omics to predict HF. For DM patients, the calcium-omics model (C-index: 81.8) outperformed other models. In conclusion, CTCS-based models combining calcium and fat-omics can predict incident HF, outperforming prediction scores based on clinical factors.Please check article title if captured correctly.YesPlease check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.Yes.

Clinical Need for Point-of-Care Testing for Diabetes in Clinical and Laboratory Improvement Amendments-Waived Settings

Point-of-care testing (POCT) has been used in multiple care settings for acute disease and, to a lesser extent, chronic disease testing. All POCT is regulated under the Clinical and Laboratory Improvement Amendments of 1988 (CLIA). CLIA-waived POCT requires no proficiency testing and can be carried out by nonlaboratory personnel. This review describes the benefits and limitations of POCT for cardiometabolic diseases and related conditions. It also explores the current U.S. regulatory environment for CLIA-waived POCT, highlighting the need for increased access.

A multimodality score strategy for assessing the risk of immune checkpoint inhibitors related cardiotoxicity

This study aimed to find the association between four common clinical biomarkers and subsequent ICICT, developing a risk scoring strategy to assess the ICICT risk. Three terminals for ICICT were : Terminal 1, cancer therapy-related cardiomyopathies; Terminal 2, myocarditis or heart failure; and Terminal 3, myocarditis, heart failure, myocardial infarction, cerebral infarction, atrial fibrillation, or death. The thresholds were : N-terminal-pro-B-type-natriuretic-peptide ≥ 125 pg/mL, cardiac troponin T ≥ 6 ng/L, high-sensitivity C-reactive protein ≥ 3 mg/L, and coronary artery calcium score > 10 U. Each of the four abnormal biomarkers received 1 point. The links between biomarkers, score stage, and ICICT were analyzed. 375 patients with a mean follow-up of 1.91 years were included. All four biomarkers measured before immunotherapy were associated with a higher risk of developing ICICT. These scores were also associated with ICICT risk. The highest risk was the very high stage (score = 4) has 7.29, 8.83, and 7.02 folder higher risk compared to low risk group for Terminal 1-3, respectively. The cumulation of incidences also showed that the higher stages of score had an earlier onset and higher incidence of ICICT. 4 biomarkers and the scoring strategy enables clinicians to assess risk easily.

Development and validation of a machine learning-based approach to identify high-risk diabetic cardiomyopathy phenotype

AIMS

Abnormalities in specific echocardiographic parameters and cardiac biomarkers have been reported among individuals with diabetes. However, a comprehensive characterization of diabetic cardiomyopathy (DbCM), a subclinical stage of myocardial abnormalities that precede the development of clinical heart failure (HF), is lacking. In this study, we developed and validated a machine learning-based clustering approach to identify the high-risk DbCM phenotype based on echocardiographic and cardiac biomarker parameters.

METHODS AND RESULTS

Among individuals with diabetes from the Atherosclerosis Risk in Communities (ARIC) cohort who were free of cardiovascular disease and other potential aetiologies of cardiomyopathy (training, n = 1199), unsupervised hierarchical clustering was performed using echocardiographic parameters and cardiac biomarkers of neurohormonal stress and chronic myocardial injury (total 25 variables). The high-risk DbCM phenotype was identified based on the incidence of HF on follow-up. A deep neural network (DeepNN) classifier was developed to predict DbCM in the ARIC training cohort and validated in an external community-based cohort (Cardiovascular Health Study [CHS]; n = 802) and an electronic health record (EHR) cohort (n = 5071). Clustering identified three phenogroups in the derivation cohort. Phenogroup-3 (n = 324, 27% of the cohort) had significantly higher 5-year HF incidence than other phenogroups (12.1% vs. 4.6% [phenogroup 2] vs. 3.1% [phenogroup 1]) and was identified as the high-risk DbCM phenotype. The key echocardiographic predictors of high-risk DbCM phenotype were higher NT-proBNP levels, increased left ventricular mass and left atrial size, and worse diastolic function. In the CHS and University of Texas (UT) Southwestern EHR validation cohorts, the DeepNN classifier identified 16% and 29% of participants with DbCM, respectively. Participants with (vs. without) high-risk DbCM phenotype in the external validation cohorts had a significantly higher incidence of HF (hazard ratio [95% confidence interval] 1.61 [1.18-2.19] in CHS and 1.34 [1.08-1.65] in the UT Southwestern EHR cohort).

CONCLUSION

Machine learning-based techniques may identify 16% to 29% of individuals with diabetes as having a high-risk DbCM phenotype who may benefit from more aggressive implementation of HF preventive strategies.

Evidence of a bi-directional relationship between heart failure and diabetes: a strategy for the detection of glucose abnormalities and diabetes prevention in patients with heart failure

Prevalence of heart failure (HF) and diabetes are markedly increasing globally. In a population of HF patients, approximately 40% have diabetes which is associated with a more severe HF, poorer cardiovascular outcomes and higher hospitalization rates for HF than HF patients without diabetes. Similar trends were shown in HF patients with prediabetes. In addition, the association between HF and renal function decline was demonstrated in patients with or without diabetes. However, the exact prevalence of dysglycemia in HF patients requires further investigation aiming to clarify the most accurate test to detect dysglycemia in this population. The relationship between HF and diabetes is complex and probably bidirectional. In one way, patients with diabetes have a more than two-fold risk of developing incident HF with reduced or preserved ejection fraction than those without diabetes. In the other way, patients with HF, when compared with those without HF, show an increased risk for the onset of diabetes due to several mechanisms including insulin resistance (IR), which makes HF emerging as a precursor for diabetes development. This article provides epidemiological evidence of undetected dysglycemia (prediabetes or diabetes) in HF patients and reviews the pathophysiological mechanisms which favor the development of IR and the risks associated with these disorders in HF patients. This review also offers a discussion of various strategies for the prevention of diabetes in HF patients, based first on fasting plasma glucose and HbA1c measurement and if normal on an oral glucose tolerance test as diagnostic tools for prediabetes and unknown diabetes that should be performed more extensively in those patients. It discusses the implementation of diabetes prevention measures and well-structured management programs for HF patients who are generally overweight or obese, as well as current pharmacotherapeutic options for prediabetes, including sodium-glucose cotransporter 2 inhibitors which are among the pillars of HF treatment and which recently showed a benefit in the reduction of incident diabetes in HF patients. Thus, there is an urgent need of routine screening for dysglycemia in all HF patients, which should contribute to reduce the incidence of diabetes and to treat earlier diabetes when already present.

Diabetic myocardial disorder. A clinical consensus statement of the Heart Failure Association of the ESC and the ESC Working Group on Myocardial & Pericardial Diseases

The association between type 2 diabetes mellitus (T2DM) and heart failure (HF) has been firmly established; however, the entity of diabetic myocardial disorder (previously called diabetic cardiomyopathy) remains a matter of debate. Diabetic myocardial disorder was originally described as the occurrence of myocardial structural/functional abnormalities associated with T2DM in the absence of coronary heart disease, hypertension and/or obesity. However, supporting evidence has been derived from experimental and small clinical studies. Only a minority of T2DM patients are recognized as having this condition in the absence of contributing factors, thereby limiting its clinical utility. Therefore, this concept is increasingly being viewed along the evolving HF trajectory, where patients with T2DM and asymptomatic structural/functional cardiac abnormalities could be considered as having pre-HF. The importance of recognizing this stage has gained interest due to the potential for current treatments to halt or delay the progression to overt HF in some patients. This document is an expert consensus statement of the Heart Failure Association of the ESC and the ESC Working Group on Myocardial & Pericardial Diseases. It summarizes contemporary understanding of the association between T2DM and HF and discuses current knowledge and uncertainties about diabetic myocardial disorder that deserve future research. It also proposes a new definition, whereby diabetic myocardial disorder is defined as systolic and/or diastolic myocardial dysfunction in the presence of diabetes. Diabetes is rarely exclusively responsible for myocardial dysfunction, but usually acts in association with obesity, arterial hypertension, chronic kidney disease and/or coronary artery disease, causing additive myocardial impairment.

Detecting heart stress using NT-proBNP in patients with type 2 diabetes mellitus and hypertension or high-normal blood pressure: a cross-sectional multicentric study

BACKGROUND

We evaluated the prevalence of "heart stress" (HS) based on NT-proBNP cut-points proposed by the 2023 Consensus of the Heart Failure Association (HFA) of the European Society of Cardiology (ESC) in asymptomatic patients with T2DM and hypertension or high-normal blood pressure (BP) eligible for SGLT2 inhibitors (SGLT2i) and/or GLP-1 receptor agonists (GLP1-RA), drugs with proven benefits on reducing the incidence of HF, hospitalizations, cardiovascular events and mortality.

METHODS

A cross-sectional multicentric study was conducted on 192 consecutive outpatients, aged ≥ 55 years, with hypertension or high-normal BP, referred to three diabetology units. NT-proBNP was collected before starting new anti-diabetic therapy. Patients with known HF were excluded, and participants were classified based on the age-adjusted NT-proBNP cut-points.

RESULTS

Mean age: 70.3 ± 7.8 years (67.5% males). Patients with obesity (BMI ≥ 30 Kg/m2): 63.8%. Median NT-proBNP: 96.0 (38.8-213.0) pg/mL. Prevalence of chronic kidney disease (CKD, eGFR < 60 mL/min/1.73m2): 32.1%. Mean arterial BP: 138.5/77.0 ± 15.8/9.9 mmHg. The NT-proBNP values, according to the proposed age-adjusted cut-points, classified 28.6% of patients as "HS likely" (organize elective echocardiography and specialist evaluation), 43.2% as "HS not likely" (a grey area, repeat NT-proBNP at six months) and 28.2% as "very unlikely HS" (repeat NT-proBNP at one year). The presence of CKD and the number of anti-hypertensive drugs, but not glycemic parameters, were independently associated with HS.

CONCLUSIONS

According to NT-proBNP, over a quarter of T2DM patients with hypertension/high-normal BP, among those eligible for SGLT2i and/or GLP1-RA, were already at risk of cardiac damage, even subclinical. Most would receive an indication to echocardiogram and be referred to a specialist, allowing the early implementation of effective strategies to prevent or delay the progression to advanced stages of cardiac disease and overt HF.

Relationship between NT-proBNP, echocardiographic abnormalities and functional status in patients with subclinical siabetic cardiomyopathy

INTRODUCTION

Persons with diabetes are at risk for developing a cardiomyopathy through several pathophysiological mechanisms independent of traditional risk factors for heart failure. Among those with diabetic cardiomyopathy (DbCM), the relationship between natriuretic peptides, cardiac structural abnormalities and functional capacity is largely unknown.

METHODS

In this prespecified subgroup analysis of the Aldose Reductase Inhibition for Stabilization of Exercise Capacity in Heart Failure (ARISE-HF) trial, 685 participants with asymptomatic DbCM underwent baseline echocardiography data, laboratory investigations, and functional assessments. Participants were stratified by N-terminal pro-B type natriuretic peptide (NT-proBNP) quartiles, and correlation with echocardiographic and functional parameters were assessed using Spearman correlation test.

RESULTS

The median NT-proBNP was 71 (Q1, Q3: 33, 135) ng/L. No association was observed between NT-proBNP concentrations and echocardiographic parameters of either diastolic or systolic dysfunction including global longitudinal strain, left ventricular ejection fraction, left ventricular mass index, left atrial volume index, E/E', or right ventricular systolic pressure. In contrast, NT-proBNP was significantly correlated with overall Kansas City Cardiomyopathy Questionnaire score (rho = - 0.10; p = 0.007), the Physical Activity Scale in the Elderly (rho = - 0.12; p = 0.004), duration of cardiopulmonary exercise testing (rho = - 0.28; p < 0.001), peak VO2 (rho = - 0.26; p < 0.001), and ratio of minute ventilation/carbon dioxide production (rho = 0.12; p = 0.002). After adjustment for known confounders, the correlation with Physical Activity Scale in the Elderly and overall Kansas City Cardiomyopathy Questionnaire score was no longer significant.

CONCLUSION

Among patients with subclinical DbCM, elevated NT-proBNP concentrations are associated with worse health status, lower activity levels, and reduced functional capacity, but not with cardiac structural abnormalities. These findings suggest that regardless of cardiac structural abnormalities, biomarker concentrations reflect important deterioration in functional capacity in affected individuals.

TRIAL REGISTRATION

ARISE-HF, NCT04083339 Date Registered August 23, 2019.

Prediction of new-onset heart failure in patients with type 2 diabetes derived from ALTITUDE and CANVAS

AIM

To create and validate a prediction model to identify patients with type 2 diabetes (T2D) at high risk of new-onset heart failure (HF), including those treated with a sodium-glucose cotransporter-2 (SGLT2) inhibitor.

METHODS

A prediction model was developed from the Aliskiren Trial in Type 2 Diabetes Using Cardiorenal Endpoints (ALTITUDE), a trial in T2D patients with albuminuria or cardiovascular disease. We included 5081 patients with baseline N-terminal pro B-type natriuretic peptide (NT-proBNP) measurement and no history of HF. The model was developed using Cox regression and validated externally in the placebo arm of the Canagliflozin Cardiovascular Assessment Study (CANVAS), which included 996 participants with T2D and established cardiovascular disease or high cardiovascular risk, and in patients treated with canagliflozin.

RESULTS

ALTITUDE participants (mean age 64 ± 9.8 years) had a median serum NT-proBNP level of 157 (25th-75th percentile 70-359) pg/mL. Higher NT-proBNP level, troponin T (TnT) level and body mass index (BMI) emerged as significant and independent predictors of new-onset HF in both cohorts. The model further contained urinary albumin-to-creatinine ratio, glycated haemoglobin, age, haematocrit, and use of calcium channel blockers. A prediction model including these variables had a C-statistic of 0.828 (95% confidence interval [CI] 0.801-0.855) in ALTITUDE and 0.800 (95% CI 0.720-0.880) in CANVAS. The C-statistic of this model increased to 0.847 (95% CI 0.792-0.902) in patients after 1 year of canagliflozin treatment.

CONCLUSION

In patients with T2D, higher NT-proBNP level, TnT level and BMI are independent and externally validated predictors of new-onset HF, including patients using an SGLT2 inhibitor. This newly developed model may identify patients at high risk of new-onset HF, contributing to early recognition and possibly prevention.

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging

Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide, with a high associated economic burden. This study aimed to assess whether artificial intelligence models incorporating clinical, stress test, and imaging parameters could predict hospitalization for acute HF exacerbation in patients undergoing SPECT/CT myocardial perfusion imaging. Methods: The HF risk prediction model was developed using data from 4,766 patients who underwent SPECT/CT at a single center (internal cohort). The algorithm used clinical risk factors, stress variables, SPECT imaging parameters, and fully automated deep learning-generated calcium scores from attenuation CT scans. The model was trained and validated using repeated hold-out (10-fold cross-validation). External validation was conducted on a separate cohort of 2,912 patients. During a median follow-up of 1.9 y, 297 patients (6%) in the internal cohort were admitted for HF exacerbation. Results: The final model demonstrated a higher area under the receiver-operating-characteristic curve (0.87 ± 0.03) for predicting HF admissions than did stress left ventricular ejection fraction (0.73 ± 0.05, P < 0.0001) or a model developed using only clinical parameters (0.81 ± 0.04, P < 0.0001). These findings were confirmed in the external validation cohort (area under the receiver-operating-characteristic curve: 0.80 ± 0.04 for final model, 0.70 ± 0.06 for stress left ventricular ejection fraction, 0.72 ± 0.05 for clinical model; P < 0.001 for all). Conclusion: Integrating SPECT myocardial perfusion imaging into an artificial intelligence-based risk assessment algorithm improves the prediction of HF hospitalization. The proposed method could enable early interventions to prevent HF hospitalizations, leading to improved patient care and better outcomes.

Prognostic implications of heart failure stages among Chinese community populations: insight from a nationwide population-based study

Background

In light of high burden of heart failure (HF) in China, studies of prognostic implication of HF stages are important. We aimed to evaluate the relationship between HF stages and mortality risk in Chinese community populations.

Methods

Nationwide representative populations aged ≥35 years (n = 23,284, mean age 56.9 years, women 53.2%) were enrolled from 2012 to 2016. According to the international HF guidelines, participants were divided into stage A, B and C, and those who did not qualify these stages were categorized as apparently-healthy group. Association between HF stages and all-cause, cardiovascular [CV] and non-CV death was evaluated using multivariable-adjusted Cox proportional regression analysis.

Findings

During a median follow-up of 4.7 years (109,902.8 person-years), 1314 deaths occurred. Age-adjusted incidence rate of all-cause death was 5.3 in apparently-healthy, 7.8 in stage A, 8.6 in stage B and 24.6 in stage C groups per 1000 person-years. In reference to apparently-healthy group, adjusted hazard ratio for all-cause death was 1.90 (95% CI: 1.47-2.45), 2.43 (95% CI: 1.89-3.13) and 6.40 (95% CI: 4.56-8.99) for stage A, B and C. Advancing HF stages were associated with increasing risks for all-cause, CV and non-CV death (P-trend <0.05). For all-cause death, population attributable fraction due to stage A, B and C were 21.2%, 33.4% and 4.9%, accounting for 1,933,385, 3,045,993 and 446,867 deaths in China in 2018.

Interpretation

Advancing HF stages were associated with increasing risk mortality. Development and implementation of early screening and targeted interventions are urgently needed to reduce HF burdens in China.

Funding

This work was supported by the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (grant 2017-I2M-1-004), the Projects in the Chinese National Science & Technology Pillar Program during the Twelfth Five-year Plan Period (No.: 2011BAI11B01), and the Project Entrusted by the National Health Commission of the People's Republic of China (NHC2020-609).

Methods to predict heart failure in diabetes patients

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is one of the leading causes of cardiovascular disease and powerful predictor for new-onset heart failure (HF).

AREAS COVERED

We focus on the relevant literature covering evidence of risk stratification based on imaging predictors and circulating biomarkers to optimize approaches to preventing HF in DM patients.

EXPERT OPINION

Multiple diagnostic algorithms based on echocardiographic parameters of cardiac remodeling including global longitudinal strain/strain rate are likely to be promising approach to justify individuals at higher risk of incident HF. Signature of cardiometabolic status may justify HF risk among T2DM individuals with low levels of natriuretic peptides, which preserve their significance in HF with clinical presentation. However, diagnostic and predictive values of conventional guideline-directed biomarker HF strategy may be non-optimal in patients with obesity and T2DM. Alternative biomarkers affecting cardiac fibrosis, inflammation, myopathy, and adipose tissue dysfunction are plausible tools for improving accuracy natriuretic peptides among T2DM patients at higher HF risk. In summary, risk identification and management of the patients with T2DM with established HF require conventional biomarkers monitoring, while the role of alternative biomarker approach among patients with multiple CV and metabolic risk factors appears to be plausible tool for improving clinical outcomes.

Epidemiology of heart failure in diabetes: a disease in disguise

Left ventricular diastolic dysfunction (LVDD) without symptoms, and heart failure (HF) with preserved ejection fraction (HFpEF) represent the most common phenotypes of HF in individuals with type 2 diabetes mellitus, and are more common than HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and left ventricular systolic dysfunction (LVSD) in these individuals. However, diagnostic criteria for HF have changed over the years, resulting in heterogeneity in the prevalence/incidence rates reported in different studies. We aimed to give an overview of the diagnosis and epidemiology of HF in type 2 diabetes, using both a narrative and systematic review approach; we focus narratively on diagnosing (using the 2021 European Society of Cardiology [ESC] guidelines) and screening for HF in type 2 diabetes. We performed an updated (2016-October 2022) systematic review and meta-analysis of studies reporting the prevalence and incidence of HF subtypes in adults ≥18 years with type 2 diabetes, using echocardiographic data. Embase and MEDLINE databases were searched and data were assessed using random-effects meta-analyses, with findings presented as forest plots. From the 5015 studies found, 209 were screened using the full-text article. In total, 57 studies were included, together with 29 studies that were identified in a prior meta-analysis; these studies reported on the prevalence of LVSD (n=25 studies, 24,460 individuals), LVDD (n=65 studies, 25,729 individuals), HFrEF (n=4 studies, 4090 individuals), HFmrEF (n=2 studies, 2442 individuals) and/or HFpEF (n=8 studies, 5292 individuals), and on HF incidence (n=7 studies, 17,935 individuals). Using Hoy et al's risk-of-bias tool, we found that the studies included generally had a high risk of bias. They showed a prevalence of 43% (95% CI 37%, 50%) for LVDD, 17% (95% CI 7%, 35%) for HFpEF, 6% (95% CI 3%, 10%) for LVSD, 7% (95% CI 3%, 15%) for HFrEF, and 12% (95% CI 7%, 22%) for HFmrEF. For LVDD, grade I was found to be most prevalent. Additionally, we reported a higher incidence rate of HFpEF (7% [95% CI 4%, 11%]) than HFrEF 4% [95% CI 3%, 7%]). The evidence is limited by the heterogeneity of the diagnostic criteria over the years. The systematic section of this review provides new insights on the prevalence/incidence of HF in type 2 diabetes, unveiling a large pre-clinical target group with LVDD/HFpEF in which disease progression could be halted by early recognition and treatment.Registration PROSPERO ID CRD42022368035.

Optimal Screening for Predicting and Preventing the Risk of Heart Failure Among Adults With Diabetes Without Atherosclerotic Cardiovascular Disease: A Pooled Cohort Analysis

BACKGROUND

The optimal approach to identify individuals with diabetes who are at a high risk for developing heart failure (HF) to inform implementation of preventive therapies is unknown, especially in those without atherosclerotic cardiovascular disease (ASCVD).

METHODS

Adults with diabetes and no HF at baseline from 7 community-based cohorts were included. Participants without ASCVD who were at high risk for developing HF were identified using 1-step screening strategies: risk score (WATCH-DM [Weight, Age, Hypertension, Creatinine, HDL-C, Diabetes Control, QRS Duration, MI, and CABG] ≥12), NT-proBNP (N-terminal pro-B-type natriuretic peptide ≥125 pg/mL), hs-cTn (high-sensitivity cardiac troponin T ≥14 ng/L; hs-cTnI ≥31 ng/L), and echocardiography-based diabetic cardiomyopathy (echo-DbCM; left atrial enlargement, left ventricular hypertrophy, or diastolic dysfunction). High-risk participants were also identified using 2-step screening strategies with a second test to identify residual risk among those deemed low risk by the first test: WATCH-DM/NT-proBNP, NT-proBNP/hs-cTn, NT-proBNP/echo-DbCM. Across screening strategies, the proportion of HF events identified, 5-year number needed to treat and number needed to screen to prevent 1 HF event with an SGLT2i (sodium-glucose cotransporter 2 inhibitor) among high-risk participants, and cost of screening were estimated.

RESULTS

The initial study cohort included 6293 participants (48.2% women), of whom 77.7% without prevalent ASCVD were evaluated with different HF screening strategies. At 5-year follow-up, 6.2% of participants without ASCVD developed incident HF. The 5-year number needed to treat to prevent 1 HF event with an SGLT2i among participants without ASCVD was 43 (95% CI, 29-72). In the cohort without ASCVD, high-risk participants identified using 1-step screening strategies had a low 5-year number needed to treat (22 for NT-proBNP to 37 for echo-DbCM). However, a substantial proportion of HF events occurred among participants identified as low risk using 1-step screening approaches (29% for echo-DbCM to 47% for hs-cTn). Two-step screening strategies captured most HF events (75-89%) in the high-risk subgroup with a comparable 5-year number needed to treat as the 1-step screening approaches (30-32). The 5-year number needed to screen to prevent 1 HF event was similar across 2-step screening strategies (45-61). However, the number of tests and associated costs were lowest for WATCH-DM/NT-proBNP ($1061) compared with other 2-step screening strategies (NT-proBNP/hs-cTn: $2894; NT-proBNP/echo-DbCM: $16 358).

CONCLUSIONS

Selective NT-proBNP testing based on the WATCH-DM score efficiently identified a high-risk primary prevention population with diabetes expected to derive marked absolute benefits from SGLT2i to prevent HF.

American Diabetes Association Professional Practice Committee, ElSayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Das SR, Ekhlaspour L, Hilliard ME, Johnson EL, Khunti K, Kosiborod MN, Lingvay I, Matfin G, McCoy RG, Perry ML, Pilla SJ, Polsky S, Prahalad P, Pratley RE, Segal AR, Seley JJ, Stanton RC, Gabbay RA. 10. Cardiovascular Disease and Risk Management: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Prioritizing the primary prevention of heart failure: Measuring, modifying and monitoring risk

With the rising incidence of heart failure (HF) and increasing burden of morbidity, mortality, and healthcare expenditures, primary prevention of HF targeting individuals in at-risk HF (Stage A) and pre-HF (Stage B) Stages has become increasingly important with the goal to decrease progression to symptomatic (Stage C) HF. Identification of risk based on traditional risk factors (e.g., cardiovascular health which can be assessed with the American Heart Association's Life's Essential 8 framework), adverse social determinants of health, inherited risk of cardiomyopathies, and identification of risk-enhancing factors, such as patients with viral disease, exposure to cardiotoxic chemotherapy, and history of adverse pregnancy outcomes should be the first step in evaluation for HF risk. Next, use of guideline-endorsed risk prediction tools such as Pooled Cohort Equations to Prevent Heart Failure provide quantification of absolute risk of HF based in traditional risk factors. Risk reduction through counseling on traditional risk factors is a core focus of implementation of prevention and may include the use of novel therapeutics that target specific pathways to reduce risk of HF, such as mineralocorticoid receptor agonists (e.g., fineronone), angiotensin-receptor/neprolysin inhibitors, and sodium glucose co-transporter-2 inhibitors. These interventions may be limited in at-risk populations who experience adverse social determinants and/or individuals who reside in rural areas. Thus, strategies like telemedicine may improve access to preventive care. Gaps in the current knowledge base for risk-based prevention of HF are highlighted to outline future research that may target approaches for risk assessment and risk-based prevention with the use of artificial intelligence, genomics-enhanced strategies, and pragmatic trials to develop a guideline-directed medical therapy approach to reduce risk among individuals with Stage A and Stage B HF.

Unveiling the Role of Biomarkers in Cardiovascular Risk Assessment and Prognosis

Cardiovascular diseases (CVDs) remain a leading cause of global morbidity and mortality, necessitating innovative approaches for accurate risk assessment and prognosis. This review explores the evolving role of biomarkers in advancing cardiovascular risk evaluation and prognostication. Utilizing cardiac biomarkers that represent diverse pathophysiological pathways has the potential to enhance risk stratification for CVD. We delve into the intricate molecular signatures indicative of cardiovascular health, focusing on established biomarkers such as troponins, natriuretic peptides, and lipid profiles while also examining emerging candidates like microRNAs and inflammatory markers. This review provides a holistic perspective on the current landscape of cardiovascular biomarkers, offering insights into their applications in risk assessment and prognosis. In evaluating the risk and prognosis of heart failure (HF), the measurement of natriuretic peptides (B-type natriuretic peptide [BNP] or N-terminal pro-B-type natriuretic peptide [NT-proBNP]) or markers of myocardial injury (cardiac troponin I [TnI] or T [TnT]) has demonstrated utility. By elucidating the synergistic interplay between traditional markers and cutting-edge technologies, this work aims to guide future research endeavors and clinical practices, ultimately contributing to more effective strategies for risk assessment and prognosis of cardiovascular disease.

Biomarkers for Heart Failure Prediction and Prevention

Heart failure (HF) is a global pandemic affecting over 64 million people worldwide. Its prevalence is on an upward trajectory, with associated increasing healthcare expenditure. Organizations including the American College of Cardiology (ACC) and the American Heart Association (AHA) have identified HF prevention as an important focus. Recently, the ACC/AHA/Heart Failure Society of America (HFSA) Guidelines on heart failure were updated with a new Class IIa, Level of Evidence B recommendation for biomarker-based screening in patients at risk of developing heart failure. In this review, we evaluate the studies that have assessed the various roles and contributions of biomarkers in the prediction and prevention of heart failure. We examined studies that have utilized biomarkers to detect cardiac dysfunction or abnormality for HF risk prediction and screening before patients develop clinical signs and symptoms of HF. We also included studies with biomarkers on prognostication and risk prediction over and above existing HF risk prediction models and studies that address the utility of changes in biomarkers over time for HF risk. We discuss studies of biomarkers to guide management and assess the efficacy of prevention strategies and multi-biomarker and multimodality approaches to improve risk prediction.

A Synopsis of the Evidence for the Science and Clinical Management of Cardiovascular-Kidney-Metabolic (CKM) Syndrome: A Scientific Statement From the American Heart Association

A growing appreciation of the pathophysiological interrelatedness of metabolic risk factors such as obesity and diabetes, chronic kidney disease, and cardiovascular disease has led to the conceptualization of cardiovascular-kidney-metabolic syndrome. The confluence of metabolic risk factors and chronic kidney disease within cardiovascular-kidney-metabolic syndrome is strongly linked to risk for adverse cardiovascular and kidney outcomes. In addition, there are unique management considerations for individuals with established cardiovascular disease and coexisting metabolic risk factors, chronic kidney disease, or both. An extensive body of literature supports our scientific understanding of, and approach to, prevention and management for individuals with cardiovascular-kidney-metabolic syndrome. However, there are critical gaps in knowledge related to cardiovascular-kidney-metabolic syndrome in terms of mechanisms of disease development, heterogeneity within clinical phenotypes, interplay between social determinants of health and biological risk factors, and accurate assessments of disease incidence in the context of competing risks. There are also key limitations in the data supporting the clinical care for cardiovascular-kidney-metabolic syndrome, particularly in terms of early-life prevention, screening for risk factors, interdisciplinary care models, optimal strategies for supporting lifestyle modification and weight loss, targeting of emerging cardioprotective and kidney-protective therapies, management of patients with both cardiovascular disease and chronic kidney disease, and the impact of systematically assessing and addressing social determinants of health. This scientific statement uses a crosswalk of major guidelines, in addition to a review of the scientific literature, to summarize the evidence and fundamental gaps related to the science, screening, prevention, and management of cardiovascular-kidney-metabolic syndrome.

Cardiovascular-Kidney-Metabolic Health: A Presidential Advisory From the American Heart Association

Cardiovascular-kidney-metabolic health reflects the interplay among metabolic risk factors, chronic kidney disease, and the cardiovascular system and has profound impacts on morbidity and mortality. There are multisystem consequences of poor cardiovascular-kidney-metabolic health, with the most significant clinical impact being the high associated incidence of cardiovascular disease events and cardiovascular mortality. There is a high prevalence of poor cardiovascular-kidney-metabolic health in the population, with a disproportionate burden seen among those with adverse social determinants of health. However, there is also a growing number of therapeutic options that favorably affect metabolic risk factors, kidney function, or both that also have cardioprotective effects. To improve cardiovascular-kidney-metabolic health and related outcomes in the population, there is a critical need for (1) more clarity on the definition of cardiovascular-kidney-metabolic syndrome; (2) an approach to cardiovascular-kidney-metabolic staging that promotes prevention across the life course; (3) prediction algorithms that include the exposures and outcomes most relevant to cardiovascular-kidney-metabolic health; and (4) strategies for the prevention and management of cardiovascular disease in relation to cardiovascular-kidney-metabolic health that reflect harmonization across major subspecialty guidelines and emerging scientific evidence. It is also critical to incorporate considerations of social determinants of health into care models for cardiovascular-kidney-metabolic syndrome and to reduce care fragmentation by facilitating approaches for patient-centered interdisciplinary care. This presidential advisory provides guidance on the definition, staging, prediction paradigms, and holistic approaches to care for patients with cardiovascular-kidney-metabolic syndrome and details a multicomponent vision for effectively and equitably enhancing cardiovascular-kidney-metabolic health in the population.

Prognostic value of high-sensitivity cardiac troponin for major adverse cardiovascular events in patients with diabetes: a systematic review and meta-analysis

Background

High-sensitivity cardiac troponin (hs-cTn) is associated with cardiovascular outcomes in the general population, but the prognostic value of hs-cTn in the diabetic population remains inconclusive. This study aimed to systematically review current evidence regarding the association between hs-cTn and the prognosis of diabetic patients.

Methods

MEDLINE, Embase, and the Cochrane Database were searched from inception to May, 2023. Observational studies that investigated the prognostic value of hs-cTn in diabetic patients were included in this meta-analysis. Studies were excluded if they did not report outcomes of interest, or urine hs-cTn were measured. Two independent investigators extracted and analyzed the data according to the PRISMA guidelines. The primary outcome was long-term major adverse cardiovascular events (MACE).

Results

We included 30 cohort studies of 62,419 diabetic patients. After a median follow-up of 5 (4.1-9.5) years, the pooled results suggested elevation of hs-cTn was associated with a significantly increased risk of MACE (adjusted hazard ratio (HR) per standard deviation (SD) change 1.15, 95% CI [1.06-1.25], I2 = 0%) and heart failure (adjusted HR per SD change 1.33, 95% CI [1.08-1.63], I2 = 0%) in patients with diabetes. No significant association was found regarding the association between elevation of hs-cTn and risk of all-cause mortality (adjusted HR per SD change 1.24, 95% CI [0.98-1.57], I2 = 0%). The results of sensitivity analyses were similar in prospective cohort studies, high-quality studies, or population without major cardiovascular comorbidities at baseline. hs-cTn may represent a strong and independent predictor of MACE and heart failure in diabetic patients. Future research is warranted to determine the appropriate cutoff value for hs-cTn with different comorbidities, for instance, diabetic nephropathy, peripheral artery diseases, etc.

How vitamins act as novel agents for ameliorating diabetic peripheral neuropathy: A comprehensive overview

Diabetic peripheral neuropathy (DPN) is a pervasive and incapacitating sequela of diabetes, affecting a significant proportion of those diagnosed with the disease, yet an effective treatment remains elusive. Vitamins have been extensively studied, emerging as a promising target for diagnosing and treating various systemic diseases, but their role in DPN is not known. This review collates and synthesizes knowledge regarding the interplay between vitamins and DPN, drawing on bibliographies from prior studies and relevant articles, and stratifying the therapeutic strategies from prophylactic to interventional. In addition, the clinical evidence supporting the use of vitamins to ameliorate DPN is also evaluated, underscoring the potential of vitamins as putative therapeutic agents. We anticipate that this review will offer novel insights for developing and applying vitamin-based therapies for DPN.

Rationale and Design of Heart Failure Prevalence and Evolution of Heart Failure in Diabetes Mellitus Type II Patients at High Risk (HF-LanDMark Study)

(1) Background: Patients with diabetes mellitus (DM) are at increased risk for heart failure (HF). Accurate data regarding the prevalence of HF stages among diabetics in Greece are scarce. (2) Aim: The present study will examine the prevalence and evolution of HF stages among patients with type II DM (T2DM) diagnosed in the past 10 years, with no previous history of HF and at high CV risk, in Greece, as well as will explore the potential determinants of the development of symptomatic HF in these patients. (3) Methods: Through a non-interventional, epidemiological, single-country, multi-center, prospective cohort study design, a sample of 300 consecutive patients will be enrolled in 11 cardiology departments that are HF centers of excellence. Patients will be either self-referred or referred by primary or secondary care physicians and will be followed for up to 24 months. Demographic, clinical, echocardiography, electrocardiography, cardiac biomarkers (troponin, NT-proBNP) and health-related quality of life questionnaire data will be recorded as well as clinical events, including mortality, HF hospitalizations and HF-related healthcare resource utilization. The primary outcomes are the proportion of patients diagnosed with symptomatic HF (ACC/AHA Stage C) at enrolment in the overall study population and the proportions of patients with HF stages A, B and C, as well as by NYHA functional classification in the overall study population. (4) Conclusions: The HF-LanDMark study is the first epidemiological study that will assess the prevalence of HF among T2DM patients in Greece that could potentially enhance prompt therapeutic interventions shown to delay the development of HF in the T2DM patient population (HF-LanDMark, Clinical Trials.gov number, NCT04482283).

Osteopontin levels correlate with severity of diabetic cardiomyopathy in early stage of diabetes

Diabetic cardiomyopathy (DbCM) is characterized by restrictive pattern and consistent risk of overt heart failure. We here focused osteopontin (OPN), which was tested independently associated with left ventricular diastolic dysfunction (LVDD). Overall, OPN increased with DbCM severity according with the presence of left atrial dilatation, LV hypertrophy and LVDD.

2023 UPDATE: Luso-Brazilian evidence-based guideline for the management of antidiabetic therapy in type 2 diabetes

BACKGROUND

The management of antidiabetic therapy in people with type 2 diabetes (T2D) has evolved beyond glycemic control. In this context, Brazil and Portugal defined a joint panel of four leading diabetes societies to update the guideline published in 2020.

METHODS

The panelists searched MEDLINE (via PubMed) for the best evidence from clinical studies on treating T2D and its cardiorenal complications. The panel searched for evidence on antidiabetic therapy in people with T2D without cardiorenal disease and in patients with T2D and atherosclerotic cardiovascular disease (ASCVD), heart failure (HF), or diabetic kidney disease (DKD). The degree of recommendation and the level of evidence were determined using predefined criteria.

RESULTS AND CONCLUSIONS

All people with T2D need to have their cardiovascular (CV) risk status stratified and HbA1c, BMI, and eGFR assessed before defining therapy. An HbA1c target of less than 7% is adequate for most adults, and a more flexible target (up to 8%) should be considered in frail older people. Non-pharmacological approaches are recommended during all phases of treatment. In treatment naïve T2D individuals without cardiorenal complications, metformin is the agent of choice when HbA1c is 7.5% or below. When HbA1c is above 7.5% to 9%, starting with dual therapy is recommended, and triple therapy may be considered. When HbA1c is above 9%, starting with dual therapyt is recommended, and triple therapy should be considered. Antidiabetic drugs with proven CV benefit (AD1) are recommended to reduce CV events if the patient is at high or very high CV risk, and antidiabetic agents with proven efficacy in weight reduction should be considered when obesity is present. If HbA1c remains above target, intensification is recommended with triple, quadruple therapy, or even insulin-based therapy. In people with T2D and established ASCVD, AD1 agents (SGLT2 inhibitors or GLP-1 RA with proven CV benefit) are initially recommended to reduce CV outcomes, and metformin or a second AD1 may be necessary to improve glycemic control if HbA1c is above the target. In T2D with HF, SGLT2 inhibitors are recommended to reduce HF hospitalizations and mortality and to improve HbA1c. In patients with DKD, SGLT2 inhibitors in combination with metformin are recommended when eGFR is above 30 mL/min/1.73 m2. SGLT2 inhibitors can be continued until end-stage kidney disease.

Predicting and preventing heart failure in type 2 diabetes

The burden of heart failure among people with type 2 diabetes is increasing globally. People with comorbid type 2 diabetes and heart failure often have worse outcomes than those with only one of these conditions-eg, higher hospitalisation and mortality rates. Therefore, it is essential to implement optimal heart failure prevention strategies for people with type 2 diabetes. A detailed understanding of the pathophysiology underlying the occurrence of heart failure in type 2 diabetes can aid clinicians in identifying relevant risk factors and lead to early interventions that can help prevent heart failure. In this Review, we discuss the pathophysiology and risk factors of heart failure in type 2 diabetes. We also review the risk assessment tools for predicting heart failure incidence in people with type 2 diabetes as well as the data from clinical trials that have assessed the efficacy of lifestyle and pharmacological interventions. Finally, we discuss the potential challenges in implementing new management approaches and offer pragmatic recommendations to help overcome these challenges.

Deficiency of Tregs in hypertension-associated left ventricular hypertrophy

Left ventricular hypertrophy (LVH) is the most common target organ damage in hypertension. Abnormal numbers or functions of CD4+ CD25+ Foxp3+ regulatory T lymphocytes (Tregs) can cause immune disorders, which participates in LVH. This study aimed to explore the role of Tregs in LVH by investigating circulating Tregs and associated cytokine levels in hypertensive patients with or without LVH. Blood samples were collected from 83 hypertensive patients without LVH (essential hypertension group, EH), 91 hypertensive patients with LVH (left ventricular hypertrophy group, LVH), and 69 normotensive controls without LVH (control group, CG). Tregs and cytokines were measured by flow cytometry and enzyme-linked immunosorbent assays. We found that circulating Tregs were significantly lower in hypertensive patients than in CG subjects. It was lower in LVH than in EH patients. No correlation between blood pressure regulation and Tregs was found in EH or LVH patients. Furthermore, Tregs in older females were lower than those in older males among LVH patients. Additionally, serum interleukin-10 (IL-10) and transforming growth factor beta 1 (TGFβ1) decreased in hypertensive patients, and interleukin-6 (IL-6) increased in LVH patients. Tregs were negatively correlated with creatine kinase, low-density lipoprotein cholesterol, apoprotein B, high-sensitivity C-reactive protein, and left ventricular mass index (LVMI) values. In general, our study demonstrates significantly decreased circulating Tregs in hypertensive LVH patients. Decreased circulating Tregs in LVH is independent of blood pressure regulation. IL-6, IL-10, and TGF-β1 are related with LVH in hypertension.

Swiss recommendations of the Society for Endocrinology and Diabetes (SGED/SSED) for the treatment of type 2 diabetes mellitus (2023)

As a first step, the authors emphasise lifestyle changes (increased physical activity, stopping smoking), blood pressure control, and lowering cholesterol). The initial medical treatment should always be a combination treatment with metformin and a sodium-glucose transporter 2 (SGLT-2) inhibitor or a glucagon-like 1 peptide (GLP-1) receptor agonist. Metformin is given first and up-titrated, followed by SGLT-2 inhibitors or GLP-1 receptor agonists. In persons with type 2 diabetes, if the initial double combination is not sufficient, a triple combination (SGLT-2 inhibitor, GLP-1 receptor agonist, and metformin) is recommended. This triple combination has not been officially tested in cardiovascular outcome trials, but there is more and more real-world experience in Europe and in the USA that proves that the triple combination with metformin, SGLT-2 inhibitor, and GLP-1 receptor agonist is the best treatment to reduce 3-point MACE, total mortality, and heart failure as compared to other combinations. The treatment with sulfonylurea is no longer recommended because of its side effects and higher mortality compared to the modern treatment with SGLT-2 inhibitors and GLP-1 receptor agonists. If the triple combination is not sufficient to reduce the HbA1c to the desired target, insulin treatment is necessary. A quarter of all patients with type 2 diabetes (sometimes misdiagnosed) require insulin treatment. If insulin deficiency is the predominant factor at the outset of type 2 diabetes, the order of medications has to be reversed: insulin first and then cardio-renal protective medications (SGLT-2 inhibitors, GLP-1 receptor agonists).

Early intervention and intensive management of patients with diabetes, cardiorenal, and metabolic diseases

Increasing rates of obesity and diabetes have driven corresponding increases in related cardiorenal and metabolic diseases. In many patients, these conditions occur together, further increasing morbidity and mortality risks to the individual. Yet all too often, the risk factors for these disorders are not addressed promptly in clinical practice, leading to irreversible pathologic progression. To address this gap, we convened a Task Force of experts in cardiology, nephrology, endocrinology, and primary care to develop recommendations for early identification and intervention in obesity, diabetes, and other cardiorenal and metabolic diseases. The recommendations include screening and diagnosis, early interventions with lifestyle, and when and how to implement medical therapies. These recommendations are organized into primary and secondary prevention along the continuum from obesity through the metabolic syndrome, prediabetes, diabetes, hypertension, dyslipidemia, nonalcoholic fatty liver disease (NAFLD), atherosclerotic cardiovascular disease (ASCVD) and atrial fibrillation, chronic kidney disease (CKD), and heart failure (HF). The goal of early and intensive intervention is primary prevention of comorbidities or secondary prevention to decrease further worsening of disease and reduce morbidity and mortality. These efforts will reduce clinical inertia and may improve patients' well-being and adherence.

Association of biomarkers and risk scores with subclinical left ventricular dysfunction in patients with type 2 diabetes mellitus

BACKGROUND

Subclinical LV dysfunction (LVD) identifies heart failure (HF) risk in type 2 diabetes mellitus (T2DM). We sought the extent to which clinical scores (ARIC-HF, WATCH-DM), natriuretic peptides (NTpBNP) and troponin (hs-TnT) were associated with subclinical LV dysfunction (LVD). These associations could inform the ability of these tests to identify which patients should undergo echocardiography.

METHODS

Participants with T2DM were prospectively recruited from three community-based populations. ARIC-HF risk at 4 years and WATCH-DM scores were calculated from clinical data. NTpBNP and hs-TnT were measured using an electro-chemiluminescence assay. All underwent a comprehensive echocardiogram. We calculated the sensitivity and specificity of clinical scores and biomarkers to identify abnormal global longitudinal strain (GLS ≥ -16%)), diastolic function (E/e' ≥ 14 or e' < 8 cm/s), left atrial volume index (LAV > 34 ml/m2) and LV hypertrophy (LV mass index > 88 g/m2 (F) > 102 g/m2(M)).

RESULTS

Of 804 participants (median age 69 years [inter-quartile range (IQR) 65-73], 36% female), clinical scores suggested significant HF risk (median ARIC-HF 8% [IQR 4-12]; WATCH-DM 10 points [IQR 8-12]), and the median NTpBNP was 50 pg/mL [IQR 25-101] and hs-TnT 9.6 pg/mL [IQR 6.8-13.6]. Abnormal GLS was present in 126 (17%), elevated E/e' in 114 (15%), impaired e' in 629 (78%), increased LAV in 351 (44%) and LV hypertrophy in 113 (14%). After adjustments for age, body-mass index, and renal function, each standard deviation increase in NTpBNP was associated with a GLS increase of 0.32 (p < 0.001) and hs-TnT increase by 0.26 (p < 0.001). Similar trends were observed with ARIC-HF (standardised β = 0.22, p < 0.001) and WATCH-DM (standardised β = 0.22, p < 0.001) in univariable analyses. However, none of the risk assessment tools provided satisfactory discrimination for abnormal GLS (AUC 63%), diastolic indices (e' AUC 54-61%) or LV mass (AUC 59-67%). At a sensitivity of 90%, there was an unacceptably low (< 50%) specificity.

CONCLUSION

Although risk assessment based on clinical scores or biomarkers would be desirable to stratify HF risk in people with T2DM, they show a weak relationship with subclinical LVD.

Derivation and External Validation of a Clinical Model to Predict Heart Failure Onset in Patients With Incident Diabetes

OBJECTIVE

Heart failure (HF) often develops in patients with diabetes and is recognized for its role in increased cardiovascular morbidity and mortality in this population. Most existing models predict risk in patients with prevalent rather than incident diabetes and fail to account for sex differences in HF risk factors. We derived sex-specific models in Ontario, Canada to predict HF at diabetes onset and externally validated these models in the U.K.

RESEARCH DESIGN AND METHODS

Retrospective cohort study using international population-based data. Our derivation cohort comprised all Ontario residents aged ≥18 years who were diagnosed with diabetes between 2009 and 2018. Our validation cohort comprised U.K. patients aged ≥35 years who were diagnosed with diabetes between 2007 and 2017. Primary outcome was incident HF. Sex-stratified multivariable Fine and Gray subdistribution hazard models were constructed, with death as a competing event.

RESULTS

A total of 348,027 Ontarians (45% women) and 54,483 U.K. residents (45% women) were included. At 1, 5, and 9 years, respectively, in the external validation cohort, the C-statistics were 0.81 (95% CI 0.79-0.84), 0.79 (0.77-0.80), and 0.78 (0.76-0.79) for the female-specific model; and 0.78 (0.75-0.80), 0.77 (0.76-0.79), and 0.77 (0.75-0.79) for the male-specific model. The models were well-calibrated. Age, rurality, hypertension duration, hemoglobin, HbA1c, and cardiovascular diseases were common predictors in both sexes. Additionally, mood disorder and alcoholism (heavy drinker) were female-specific predictors, while income and liver disease were male-specific predictors.

CONCLUSIONS

Our findings highlight the importance of developing sex-specific models and represent an important step toward personalized lifestyle and pharmacologic prevention of future HF development.

Heart Failure: An Underappreciated Complication of Diabetes. A Consensus Report of the American Diabetes Association

Heart failure (HF) has been recognized as a common complication of diabetes, with a prevalence of up to 22% in individuals with diabetes and increasing incidence rates. Data also suggest that HF may develop in individuals with diabetes even in the absence of hypertension, coronary heart disease, or valvular heart disease and, as such, represents a major cardiovascular complication in this vulnerable population; HF may also be the first presentation of cardiovascular disease in many individuals with diabetes. Given that during the past decade, the prevalence of diabetes (particularly type 2 diabetes) has risen by 30% globally (with prevalence expected to increase further), the burden of HF on the health care system will continue to rise. The scope of this American Diabetes Association consensus report with designated representation from the American College of Cardiology is to provide clear guidance to practitioners on the best approaches for screening and diagnosing HF in individuals with diabetes or prediabetes, with the goal to ensure access to optimal, evidence-based management for all and to mitigate the risks of serious complications, leveraging prior policy statements by the American College of Cardiology and American Heart Association.

Biomarkers for the prediction of heart failure and cardiovascular events in patients with type 2 diabetes: a position statement from the Heart Failure Association of the European Society of Cardiology

Knowledge on risk predictors of incident heart failure (HF) in patients with type 2 diabetes (T2D) is crucial given the frequent coexistence of the two conditions and the fact that T2D doubles the risk of incident HF. In addition, HF is increasingly being recognized as an important endpoint in trials in T2D. On the other hand, the diagnostic and prognostic performance of established cardiovascular biomarkers may be modified by the presence of T2D. The present position paper, derived by an expert panel workshop organized by the Heart Failure Association of the European Society of Cardiology, summarizes the current knowledge and gaps in evidence regarding the use of a series of different biomarkers, reflecting various pathogenic pathways, for the prediction of incident HF and cardiovascular events in patients with T2D and in those with established HF and T2D.

Validation of the WATCH-DM and TRS-HFDM Risk Scores to Predict the Risk of Incident Hospitalization for Heart Failure Among Adults With Type 2 Diabetes: A Multicohort Analysis

Background The WATCH-DM (weight [body mass index], age, hypertension, creatinine, high-density lipoprotein cholesterol, diabetes control [fasting plasma glucose], ECG QRS duration, myocardial infarction, and coronary artery bypass grafting) and TRS-HF_DM (Thrombolysis in Myocardial Infarction [TIMI] risk score for heart failure in diabetes) risk scores were developed to predict risk of heart failure (HF) among individuals with type 2 diabetes. WATCH-DM was developed to predict incident HF, whereas TRS-HF_DM predicts HF hospitalization among patients with and without a prior HF history. We evaluated the model performance of both scores to predict incident HF events among patients with type 2 diabetes and no history of HF hospitalization across different cohorts and clinical settings with varying baseline risk. Methods and Results Incident HF risk was estimated by the integer-based WATCH-DM and TRS-HF_DM scores in participants with type 2 diabetes free of baseline HF from 2 randomized clinical trials (TECOS [Trial Evaluating Cardiovascular Outcomes With Sitagliptin], N=12 028; and Look AHEAD [Look Action for Health in Diabetes] trial, N=4867). The integer-based WATCH-DM score was also validated in electronic health record data from a single large health care system (N=7475). Model discrimination was assessed by the Harrell concordance index and calibration by the Greenwood-Nam-D'Agostino statistic. HF incidence rate was 7.5, 3.9, and 4.1 per 1000 person-years in the TECOS, Look AHEAD trial, and electronic health record cohorts, respectively. Integer-based WATCH-DM and TRS-HF_DM scores had similar discrimination and calibration for predicting 5-year HF risk in the Look AHEAD trial cohort (concordance indexes=0.70; Greenwood-Nam-D'Agostino P>0.30 for both). Both scores had lower discrimination and underpredicted HF risk in the TECOS cohort (concordance indexes=0.65 and 0.66, respectively; Greenwood-Nam-D'Agostino P<0.001 for both). In the electronic health record cohort, the integer-based WATCH-DM score demonstrated a concordance index of 0.73 with adequate calibration (Greenwood-Nam-D'Agostino P=0.96). TRS-HF_DM score could not be validated in the electronic health record because of unavailability of data on urine albumin/creatinine ratio in most patients in the contemporary clinical practice. Conclusions The WATCH-DM and TRS-HF_DM risk scores can discriminate risk of HF among intermediate-risk populations with type 2 diabetes.

Sex and Race Differences in N-Terminal Pro-B-type Natriuretic Peptide Concentration and Absolute Risk of Heart Failure in the Community

Importance

Sex- and race-based differences in N-terminal pro-B-type natriuretic peptide (NT-proBNP) concentrations are poorly understood. Clinical decisions are often informed by absolute-as opposed to relative-risk, but absolute risk of incident heart failure (HF) associated with NT-proBNP concentration across these important demographic categories is unclear.

Objective

To determine whether physiologic determinants of NT-proBNP concentrations account for sex and race differences, and to more uniformly predict HF risk using NT-proBNP in these demographic subgroups.

Design, Setting, and Participants

In the longitudinal Atherosclerosis Risk in Communities epidemiologic prospective community-based cohort study, the association of NT-proBNP concentration with relative and absolute risk of HF by sex- and race-based categories was assessed at study visit 2 (1990-1992) and study visit 5 (2011-2013) using Cox and Poisson regression. These data were analyzed from June 2018 to October 2021. The contribution of clinical, anthropometric, echocardiographic, and laboratory parameters to sex- and race-based differences in NT-proBNP concentration was assessed at visit 5 using linear regression. Participants included were free of HF in midlife (visit 2; a total of 12 750 participants) and late life (visit 5; a total of 5191 participants).

Exposures

NT-proBNP concentration.

Main Outcomes and Measures

Incident HF or death.

Results

Among the 5191 HF-free participants at visit 5, the mean (SD) age was 76.0 (5.2) years, 2104 (41%) were male, 1043 (20%) were Black, and the median (IQR) NT-proBNP concentration was 124 (64-239) pg/. In both midlife and late life, NT-proBNP concentration was lowest in Black men (median [IQR] concentration: visit 2, 30 [14-67] pg/mL; visit 5, 74 [34-153] pg/mL) and highest in White women (median [IQR] concentration: visit 2, 70 [42-111] pg/mL; visit, 5, 154 [82-268] pg/mL). Sex and race differences in NT-proBNP concentration persisted after accounting for age, income, education, area deprivation index, cardiovascular diseases, left ventricular structure (LV), LV function, LV wall stress, weight and fat mass, and estimated glomerular filtration rate. Substantial differences in the absolute risk of incident HF or death existed across the sex- and race-based categories at any NT-proBNP concentration (eg, 7-fold [rate ratio, 6.7; 95% CI, 4.6-9.9] and 3-fold [rate ratio, 2.7; 95% CI, 1.7-4.1] difference at visit 2 and visit 5, respectively, at guideline-recommended thresholds) with higher risk consistently observed among Black men and lower risk in White women. Results were replicated in a cohort of participants from the Cardiovascular Health Study.

Conclusions and Relevance

In this study, sex- and race-based differences in NT-proBNP persisted after accounting for known physiologic determinants. Absolute risk associated with a given value of NT-proBNP varied substantially by sex and race. Consideration of NT-proBNP values in the context of sex and race allows for more uniform prediction of absolute risk across important demographic subgroups.

New strategies and therapies for the prevention of heart failure in high-risk patients

Despite declines in total cardiovascular mortality rates in the United States, heart failure (HF) mortality rates as well as hospitalizations and readmissions have increased in the past decade. Increases have been relatively higher among young and middle-aged adults (<65 years). Therefore, identification of individuals HF at-risk (Stage A) or with pre-HF (Stage B) before the onset of overt clinical signs and symptoms (Stage C) is urgently needed. Multivariate risk models (e.g., Pooled Cohort Equations to Prevent Heart Failure [PCP-HF]) have been externally validated in diverse populations and endorsed by the 2022 HF Guidelines to apply a risk-based framework for the prevention of HF. However, traditional risk factors included in the PCP-HF model only account for half of an individual's lifetime risk of HF; novel risk factors (e.g., adverse pregnancy outcomes, impaired lung health, COVID-19) are emerging as important risk-enhancing factors that need to be accounted for in personalized approaches to prevention. In addition to determining the role of novel risk-enhancing factors, integration of social determinants of health (SDoH) in identifying and addressing HF risk is needed to transform the current clinical paradigm for the prevention of HF. Comprehensive strategies to prevent the progression of HF must incorporate pharmacotherapies (e.g., sodium glucose co-transporter-2 inhibitors that have also been termed the "statins" of HF prevention), intensive blood pressure lowering, and heart-healthy behaviors. Future directions include investigation of novel prediction models leveraging machine learning, integration of risk-enhancing factors and SDoH, and equitable approaches to interventions for risk-based prevention of HF.

Left Ventricular Hypertrophy and Biomarkers of Cardiac Damage and Stress in Aortic Stenosis

Background Left ventricular hypertrophy (LVH) is associated with increased mortality risk and rehospitalization after transcatheter aortic valve replacement among those with severe aortic stenosis. Whether cardiac troponin (cTnT) and NT-proBNP (N-terminal pro-B-type natriuretic peptide) risk stratify patients with aortic stenosis and without LVH is unknown. Methods and Results In a multicenter prospective registry of 923 patients with severe aortic stenosis undergoing transcatheter aortic valve replacement, we included 674 with core-laboratory-measured LV mass index, cTnT, and NT-proBNP. LVH was defined by sex-specific guideline cut-offs and elevated biomarker levels were based on age and sex cut-offs. Adjusted Cox proportional hazards models evaluated associations between LVH and biomarkers and all-cause death out to 5 years. Elevated cTnT and NT-proBNP were present in 82% and 86% of patients with moderate/severe LVH, respectively, as compared with 66% and 69% of patients with no/mild LVH, respectively (P<0.001 for each). After adjustment, compared with no/mild LVH, moderate/severe LVH was associated with an increased hazard of mortality (adjusted hazard ratio [aHR], 1.34; 95% CI 1.01-1.77, P=0.043). cTnT and NT-proBNP each risk stratified patients with moderate/severe LVH (P<0.05). In a model with both biomarkers and LVH included, elevated cTnT (aHR, 2.08; 95% CI 1.45-3.00, P<0.001) and elevated NT-proBNP (aHR, 1.46; 95% CI 1.00-2.11, P=0.049) were each associated with increased mortality risk, whereas moderate/severe LVH was not (P=0.15). Conclusions Elevations in circulating cTnT and NT-proBNP are more common as LVH becomes more pronounced but are also observed in those with no/minimal LVH. As measures of maladaptive remodeling and cardiac injury, cTnT and NT-proBNP predict post-transcatheter aortic valve replacement mortality better than LV mass index. These findings may have important implications for risk stratification and treatment of patients with aortic stenosis.

Team-based strategies to prevent heart failure

PURPOSE OF REVIEW

The burden of heart failure (HF) in the United States and worldwide is projected to rise. Prevention of HF can curb the burden of this chronic syndrome, but current approaches are limited. This review discusses team-based strategies aimed to prevent HF.

RECENT FINDINGS

Individuals at high risk for developing HF can be identified using HF risk scores, biomarkers, and cardiac imaging. Electronic medical records (EMR) can integrate clinical data to estimate HF risk and identify individuals who may benefit most from preventive therapies. Team-based interventions can lead to enhanced adherence to medications, optimization of medical management, and control of risk factors. Multifaceted interventions involve EMR-based strategies, pharmacist- and nurse-led initiatives, involvement of community personnel, polypills, and digital solutions.

SUMMARY

Team-based strategies aimed to prevent HF incorporate a broad group of personnel and tools. Despite implementation challenges, existing resources can be efficiently utilized to facilitate team-based approaches to potentially reduce the burden of HF.